# Copyright 2019 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#            http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Thin wrapper around imitation.scripts.train_adversarial."""

import os

from imitation.scripts import train_adversarial

from evaluating_rewards import serialize
from evaluating_rewards.scripts import script_utils


@train_adversarial.train_ex.named_config
def point_maze():
    """IRL config for PointMaze environment."""
    env_name = "imitation/PointMazeLeftVel-v0"
    rollout_path = os.path.join(
        serialize.get_output_dir(),
        "train_experts/ground_truth/20201203_105631_297835/imitation_PointMazeLeftVel-v0",
        "evaluating_rewards_PointMazeGroundTruthWithCtrl-v0/best/rollouts/final.pkl",
    )
    total_timesteps = 1e6
    _ = locals()
    del _


if __name__ == "__main__":
    script_utils.add_logging_config(train_adversarial.train_ex, "train_adversarial")
    script_utils.experiment_main(
        train_adversarial.train_ex, "train_adversarial", sacred_symlink=False
    )
